Answer / Kundan Kumar

The bias-variance trade-off is a fundamental problem in machine learning that deals with finding the right balance between an overly complex model (high bias and low variance) and an overfitting model (low bias and high variance). A model with high bias makes incorrect assumptions, leading to poor performance on unseen data. On the other hand, a model with high variance fits the training data too closely, also leading to poor performance on unseen data.

What do you mean by ensemble learning?

1 Answers  

---

What is regression in machine learning with example?

1 Answers  

---

Why is Python better for machine learning?

1 Answers  

---

Explain Classification and Regression?

1 Answers  

---

How do you ensure you're not overfitting with a model?

1 Answers  

---

Explain the importance of bayes theorem?

1 Answers  

---

What Are The Steps Involved In Machine Learning Project?

1 Answers  

---

Which is the best language for machine learning?

1 Answers  

---

Explain how do you handle missing or corrupted data in a dataset?

1 Answers  

---

Explain the two components of Bayesian logic program?

1 Answers  

---

Tell us when should you use classification over regression?

1 Answers  

---

What are the different methods for Sequential Supervised Learning?

1 Answers  

---